Senior Data Scientist

Minor Hotels Europe and Americas

Senior Data Scientist designing and implementing ML/NLP models for business use cases at Capgemini Invent. Collaborating with stakeholders and driving innovative AI/ML solutions.

Posted 7/29/2026full-timeNoida • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and implementing ML/NLP models, with a strong focus on predictive modeling, data analysis, and model deployment using MLOps practices. Collaborates effectively with stakeholders to deliver innovative AI/ML solutions while ensuring compliance and quality.

Highest-signal resume keywords

ML/NLP Model DevelopmentPredictive ModelingMLOps ConceptsDeep Learning TechniquesData Analysis and Preprocessing

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Predictive ModelingRegression MethodsClassification MethodsEnsemble MethodsDeep LearningCNNRNNLSTMNLP TechniquesClustering

Soft Skills

CollaborationStakeholder EngagementKnowledge Sharing

Tools & Technologies

ML PipelinesMLOps PracticesCloud EnvironmentsOn-Premises EnvironmentsVector Databases

Industry Keywords

AI SolutionsGenerative AIRAG PipelinesRecommendation SystemsOCRSpeech RecognitionComputer Vision

Tech Stack

Tools & technologies

AWSAzureCassandraCloudGoogle Cloud PlatformMongoDBMySQLNoSQLNumpyOraclePandasPythonPyTorchRDBMSScikit-LearnSparkSQLTableauTensorflow

About the role

Key responsibilities & impact

Develop and implement ML/NLP models for various business use cases
Analyze and preprocess data, ensuring quality and security compliance
Collaborate with stakeholders to understand requirements and deliver solutions
Support ML asset creation and contribute to knowledge sharing within the team
Assist in deploying models using ML pipelines and MLOps practices on cloud or on-premises environments
Stay updated with industry trends and propose innovative AI/ML solutions.

Requirements

What you’ll need

Predictive modeling using regression, classification, and ensemble methods
Basic experience with deep learning (CNN, RNN, LSTM) and NLP techniques (sentiment analysis, text classification)
Familiarity with clustering, dimensionality reduction, and recommendation systems
Exposure to OCR, speech recognition, or computer vision is a plus
Understanding of model deployment and MLOps concepts
Exposure to Generative AI concepts and building LLM-based applications
Understanding of RAG pipelines and vector databases.

Benefits

Comp & perks

Flexible work arrangements
Career growth programs
Certifications in latest technologies